Corey Haines Product Marketing Context Skill

Publisher: Corey Haines · Editorial profile by AI Tools Ratings · Review method

Not runtime tested; source-document review only. Referenced scripts were not executed or comprehensively audited. No security certification.

What task is this skill designed for?

Create product context from an approved directory brief and record unresolved questions.

What input and output should you expect?

Input: Verified features, intended users, alternatives, positioning decisions, approved proof points and known gaps.

Output: A structured context document for review and reuse; expected, not independently tested. It is not independent market validation.

What does it need to run?

An Agent Skills-capable client that can read approved project material and write the intended context file. No marketing account connection is needed for a local draft.

Publisher README declares support for Agent Skills clients including Claude Code, Codex and Cursor. This is author-declared, not independently runtime tested.

How should you approach installation?

1. Inspect the pinned source, license and task-specific reference files before installing anything.
2. Follow the publisher README guidance for your actual client; no installation command or cross-client compatibility was independently tested here.
3. Try the illustrative prompt with synthetic input in a separate folder, inspect the output against the checklist and approve external actions separately.

Installation guide: discovery, dependencies and runtime checks

What files, accounts or data can it access?

Reads product and audience documents and writes reusable project context. Other skills may load it later; omit secrets and raw customer records.

What does the skill cost?

The inspected source license is MIT. Agent subscriptions, model usage, dependencies and external services have separate costs and terms. No paid runtime was tested.

What are its limits and alternatives?

Stale pricing or unproven differentiation can propagate across later campaigns. Preserve evidence dates, distinguish facts from decisions and assign responsibility for updates.

Use a one-off brief for a single task. This workflow is useful when multiple campaigns or skills need a shared reviewed evidence base.

What could you ask in a small trial?

Try this with a small sample:

Create product context from this synthetic brief. Separate verified facts, positioning choices and unanswered questions. Do not invent customer research, revenue or competitive advantages.

How would you verify the result?

1. Trace proof points to approved dated evidence.
2. Flag unknown segments, prices and differentiation.
3. Review the saved context before another workflow relies on it.

Use a baseline and record acceptance evidence before treating a successful task as a reliable workflow.

Which source and license were checked?

Read the reviewed SKILL.md at its pinned commit · Complete reviewed folder

Repository and current publisher guidance

Checked: 2026-10-21

MIT — identified in LICENSE at the reviewed commit. Dependencies and third-party assets may have separate terms. License evidence

Report an error, license concern or request a new review.